DCATlike

DCATlike is a conceptual framework and a set of best practices for describing datasets, often referred to as data catalogs. It is not a formal specification like DCAT (Data Catalog Vocabulary), but rather an approach that draws inspiration from DCAT's principles of making data discoverable and understandable. The core idea behind DCATlike is to provide a standardized way to represent metadata about datasets, enabling users and machines to effectively find, access, and utilize them.

The principles of DCATlike emphasize the importance of describing key aspects of a dataset, such as its title, description, creator, publisher, date of publication, format, and access methods. It also encourages the inclusion of information about the data's scope, quality, and licensing. By adopting a DCATlike approach, organizations can improve the interoperability and reusability of their data assets. This facilitates data sharing, promotes open data initiatives, and supports data-driven decision-making.

While DCATlike itself doesn't prescribe a specific technology or schema, it often aligns with existing metadata standards and vocabularies. Implementations might use RDF, JSON-LD, or other structured data formats to represent the metadata. The goal is to achieve a common understanding of data, regardless of where it is stored or how it is managed, thereby enhancing the overall data landscape.